Evidence map›Paper›PMID 39084381›Full record

ArticleThe Science of the total environment2024

Advancements in mapping areas suitable for wetland habitats across the conterminous United States.

Lauren Krohmer, Elijah Heetderks, Jeremy Baynes, Anne Neale

Abstract read
In one paragraph

Article in The Science of the total environment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Lauren KrohmerOak Ridge Associated Universities supporting U.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA.
Elijah HeetderksOak Ridge Associated Universities supporting U.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA.
Jeremy BaynesU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Environmental Pathways Modeling Branch (EPMB), 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA. Electronic address: Baynes.Jeremy@epa.gov.
Anne NealeU.S. Environmental Protection Agency (EPA), Center for Public Health and Environmental Assessment (CPHEA), Environmental Pathways Modeling Branch (EPMB), 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Wetland habitats provide critical ecosystem services to the surrounding landscape, including nutrient and pollutant retention, flood mitigation, and carbon storage. Wetland connectivity to water bodies and related ecosystems is critical in habitat sustainability, but there are limited resources for landscape-level wetland planning. Considering the network connectivity of an ecosystem type can derive different benefits to the natural and built environment, as well as human health. The value that wetlands provide, along with incentive programs and conservation goals mandated by the government require new and improved wetland spatial data. Utilizing high quality, publicly available data, this study finds that the amount of land in the United States that could support built or restored wetlands is more than double the area of mapped existing wetlands. This study uses 17 input variables (i.e., features extracted from remotely sensed data and auxiliary datasets) at the 10-m resolution and the National Wetlands Inventory to train a random forest model to identify areas that may support a wetland habitat, or potential wetland areas. Models were calculated for each of 18 two-digit hydrologic units that encompass the conterminous United States, and model overall accuracy ranged from 78.0 % to 89.8 %. The models predicted that 21.1 % of the conterminous United States can be categorized as potential wetland area. Selecting input variables to predict areas with wetland potential, rather than to identify existing wetlands, using the random forest algorithm can be transferred to other locations, scales, and ecosystem types. Visualizing potential wetland areas using input data at the 10-m resolution and enhanced methodology improves previous work, as even slight changes in topography, soils, and landscape features can determine ecosystem connections. This product can be used to better place wetland restoration projects to serve ecosystem- and community-wide health by ensuring ecosystem success and targeting areas that face increased climate change impacts.

Indexed as

Conservation of Natural ResourcesWetlandsEcosystemEnvironmental MonitoringUnited StatesEcosystem services (and/or nature-based solutions)Machine learningPredictive modelingRestoration (and/or conservation)Training data

Identifiers

PMID39084381
PMCPMC11998124

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.